Intermediate Machine Learning Engineer

About Sybrin Sybrin is a leading IT software development company specialising in innovative solutions tailored to meet the evolving needs of businesses across various sectors. Our mission is to empower businesses with cutting‑edge technology solutions that drive efficiency, enhance customer experiences, and facilitate growth. At Sybrin we pride ourselves on delivering high‑quality products and secure solutions, thanks in part to the combination of the ISO 9001 for Quality Management System and ISO/IEC 27001 for Information Security Management System certifications, and our commitment to data protection, demonstrated by our implementation of ISO/IEC 27701 Privacy Information Management System. As an employee of Sybrin, you will be expected to familiarise yourself with the contents of the Integrated Management System, as well as undergo periodic training to better understand your unique role in the security, quality, and privacy ecosystem within Sybrin, and uphold the principles in Sybrin’s Integrated Management System. Role Overview This role will be responsible for developing and implementing machine learning solutions that integrate seamlessly with the overarching product space being developed within the company. This involves designing, building, and deploying machine learning models and algorithms that address complex business problems and enhance the company's product offerings. Qualifications and Experience Bachelor’s degree in Computer Science, Data Science, Statistics, or a related field. Minimum of 3‑5 years’ experience. Reporting Line: Machine Learning Team Lead Key Responsibilities Designing and developing machine learning models and algorithms. Performing data preprocessing, data analysis and feature engineering. Evaluating model performance and tuning hyperparameters for optimization. Collaborating with data scientists, software engineers, and stakeholders to define project requirements. Implementing and deploying machine learning models into production. Conducting code reviews to ensure code quality and best practices. Debugging and resolving issues related to machine learning models and data pipelines. Creating and maintaining technical documentation for machine learning projects. Staying updated with the latest advancements in machine learning and data science. Critical Technical and Behavioural Skills Required Machine Learning Frameworks: Experience with frameworks such PyTorch, TensorFlow, TensorFlow Light, Oynx and Scikit-learn. Data Labelling: Generation of data sets, using data labelling tools such as Roboflow or CVat. Data Processing: Proficiency in using libraries such as Pandas, NumPy, and SciPy for data manipulation and analysis. Algorithms: Understanding of key machine learning and statistical algorithms including regression, classification, clustering and neural networks. Model Development: Experience in developing, training, and evaluating machine learning models. Model Deployment: Basic knowledge of deploying models using FastAPI and Docker. APIs: Understanding of creating RESTful APIs to integrate ML models into applications. Version Control Systems: Proficient in using Git and DVC for version control. Data Visualization: Skills in using libraries such as Matplotlib, Seaborn, and Plotly. Cloud Platforms: Some experience with the machine learning aspects of cloud services such as AWS, Google Cloud, or Azure. Additional Tools: Experience with a integrated development environments (IDEs) like PyCharm or VS Code. Analytical thinking Problem-solving Effective communication Working knowledge of the principles in ISO 9001:2015 (Quality Management System), ISO/IEC 27001:2022 (Information security, cybersecurity, and privacy management System), ISO/IEC 27701:2019 (Privacy Information Management System), POPIA, GDPR. #J-18808-Ljbffr